Intro
Preface
Organization
Consent as a Foundation for Responsible Autonomy (Abstracts)
Contents
Designing International Humanitarian Law into Military Autonomous Devices*-12pt
1 Introduction
2 The Law and the Operational Framework
2.1 The Targeting Cycle
2.2 Integrating the Law into the Cycle
3 Timing and Application of Legal Tests
4 The General Framework of the Autonomous Targeting System
5 The Structure of the System
5.1 The Basics of the Model
5.2 The Structure
6 Discussion and Conclusions
References

Epistemic Diversity and Explanatory Adequacy in Distributed Information Processing*-12pt
1 Introduction
2 Background: DIP, RTSI and Plato's Cave
2.1 Distributed Information Processing Units (DIPs)
2.2 Regulatory Theory of Social Influence (RTSI)
2.3 Problem Specification
3 Experimental Design
3.1 Initial Conditions for the DIP (Independent Variables)
3.2 Epistemic Condition and Explanatory Adequacy
4 Formal Specification
4.1 The Environment
4.2 Agent Specification
4.3 Algorithm
5 Experimental Results
5.1 Experiment 1: Static and Dynamic Populations

5.2 Dynamic Population, Progressive Addition, non-Persistence
5.3 Dynamic Population, Progressive Addition, Persistence
5.4 Summary of Experiments
6 Related and Further Research
7 Summary and Conclusion
References
The Complexity of Norm Synthesis and Revision
1 Introduction
2 Preliminaries
3 Complexity of Norm Synthesis
3.1 Prohibition Synthesis
3.2 Obligation Synthesis
4 Complexity of Synthesising a Set of Norms
5 Complexity of Minimal Revision
5.1 Complexity of Minimal Prohibition Revision
5.2 Complexity of Minimal Obligation Revision

6 Related Work
7 Conclusions
References
Embracing AWKWARD! Real-Time Adjustment of Reactive Plans Using Social Norms
1 Introduction
2 Background
2.1 Behaviour Oriented Design
2.2 OperA
3 The AWKWARD Architecture
3.1 The AWKWARD Planner
3.2 The OperA Module
3.3 Behaviour Library
4 Implementation in DOTA2
4.1 DOTA2
4.2 The Reactive Planner Module and Behaviour Library
4.3 The OperA Module Implementation
5 Results
6 Related Work
6.1 Behaviour-Based AI
6.2 Normative Agents and Self-organisation
6.3 Hybrid Approaches with Reactive Planning

7 Conclusions and Future Work
References
Self-learning Governance of Black-Box Multi-Agent Systems
1 Introduction
1.1 Motivation
1.2 Illustration of the Governance Approach
1.3 Contribution
2 Related Work
3 Model
3.1 Notation
3.2 Multi-Agent System
3.3 Governance
3.4 Sequence of Actions in a GMAS
3.5 Degree of Restriction
4 Model Analysis
4.1 Fairness
4.2 Learning
4.3 Stationarity
5 Experimental Evidence
5.1 The Dining Diplomats' Problem
5.2 Reward Functions
5.3 Configurations
5.4 Frameworks and Algorithms
5.5 Reproducibility